{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:SVEE2DA43X4KPJZ3MZNW2HDP66","short_pith_number":"pith:SVEE2DA4","canonical_record":{"source":{"id":"1506.08754","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2015-06-29T17:50:20Z","cross_cats_sorted":["cs.CY"],"title_canon_sha256":"e847c3133d15a8568fdc45d171b27b06fe53d5a5cfa8e1785a8731dd17c61ca5","abstract_canon_sha256":"7959189787e87702e68fe49c2838e24613c1ca05222f3e572cd68bcc4d3e01da"},"schema_version":"1.0"},"canonical_sha256":"95484d0c1cddf8a7a73b665b6d1c6ff7a5e9523c395ee325d34898261055c417","source":{"kind":"arxiv","id":"1506.08754","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1506.08754","created_at":"2026-05-18T00:58:35Z"},{"alias_kind":"arxiv_version","alias_value":"1506.08754v2","created_at":"2026-05-18T00:58:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1506.08754","created_at":"2026-05-18T00:58:35Z"},{"alias_kind":"pith_short_12","alias_value":"SVEE2DA43X4K","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_16","alias_value":"SVEE2DA43X4KPJZ3","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_8","alias_value":"SVEE2DA4","created_at":"2026-05-18T12:29:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:SVEE2DA43X4KPJZ3MZNW2HDP66","target":"record","payload":{"canonical_record":{"source":{"id":"1506.08754","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2015-06-29T17:50:20Z","cross_cats_sorted":["cs.CY"],"title_canon_sha256":"e847c3133d15a8568fdc45d171b27b06fe53d5a5cfa8e1785a8731dd17c61ca5","abstract_canon_sha256":"7959189787e87702e68fe49c2838e24613c1ca05222f3e572cd68bcc4d3e01da"},"schema_version":"1.0"},"canonical_sha256":"95484d0c1cddf8a7a73b665b6d1c6ff7a5e9523c395ee325d34898261055c417","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:58:35.389927Z","signature_b64":"yBcHM5g13LZbtYg7anuDl9xZzaWhROeKFRppRTWkyygBH3Ay6aQ5y3uODIqV6kIDMx5yOephTaLXoaqVKeiDBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"95484d0c1cddf8a7a73b665b6d1c6ff7a5e9523c395ee325d34898261055c417","last_reissued_at":"2026-05-18T00:58:35.389279Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:58:35.389279Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1506.08754","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:58:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uIKUVLBPMLbd/jZskDOJGCSimYrkzgOFiGRrUX40E0dioOqAuPZXX5qXpwU8LiOCXM7p1jzmTXrw+J2BEmuaCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T19:18:30.930352Z"},"content_sha256":"d6c8bbf2d454572dd3683026ddb1de7278ccd018a93f25fc0bb5b48ec4cdf816","schema_version":"1.0","event_id":"sha256:d6c8bbf2d454572dd3683026ddb1de7278ccd018a93f25fc0bb5b48ec4cdf816"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:SVEE2DA43X4KPJZ3MZNW2HDP66","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving Big Data Visual Analytics with Interactive Virtual Reality","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CY"],"primary_cat":"cs.HC","authors_text":"Andrew Moran, Jeremy Kepner, Matthew Hubbell, Vijay Gadepally","submitted_at":"2015-06-29T17:50:20Z","abstract_excerpt":"For decades, the growth and volume of digital data collection has made it challenging to digest large volumes of information and extract underlying structure. Coined 'Big Data', massive amounts of information has quite often been gathered inconsistently (e.g from many sources, of various forms, at different rates, etc.). These factors impede the practices of not only processing data, but also analyzing and displaying it in an efficient manner to the user. Many efforts have been completed in the data mining and visual analytics community to create effective ways to further improve analysis and "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1506.08754","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:58:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OAP8k2402SmK/Lb3u8pl78gl5JpVUd36wWNtI4fkRunSaDD8beWFRegVxEp5OJDPCREuF9FOzKPHZ+cWcdnuAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T19:18:30.931002Z"},"content_sha256":"10d4b02fe1eab765842afb941fe850963d613be2a93da91d35c7bc2ee63fef50","schema_version":"1.0","event_id":"sha256:10d4b02fe1eab765842afb941fe850963d613be2a93da91d35c7bc2ee63fef50"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SVEE2DA43X4KPJZ3MZNW2HDP66/bundle.json","state_url":"https://pith.science/pith/SVEE2DA43X4KPJZ3MZNW2HDP66/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SVEE2DA43X4KPJZ3MZNW2HDP66/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-06T19:18:30Z","links":{"resolver":"https://pith.science/pith/SVEE2DA43X4KPJZ3MZNW2HDP66","bundle":"https://pith.science/pith/SVEE2DA43X4KPJZ3MZNW2HDP66/bundle.json","state":"https://pith.science/pith/SVEE2DA43X4KPJZ3MZNW2HDP66/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SVEE2DA43X4KPJZ3MZNW2HDP66/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:SVEE2DA43X4KPJZ3MZNW2HDP66","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"7959189787e87702e68fe49c2838e24613c1ca05222f3e572cd68bcc4d3e01da","cross_cats_sorted":["cs.CY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2015-06-29T17:50:20Z","title_canon_sha256":"e847c3133d15a8568fdc45d171b27b06fe53d5a5cfa8e1785a8731dd17c61ca5"},"schema_version":"1.0","source":{"id":"1506.08754","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1506.08754","created_at":"2026-05-18T00:58:35Z"},{"alias_kind":"arxiv_version","alias_value":"1506.08754v2","created_at":"2026-05-18T00:58:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1506.08754","created_at":"2026-05-18T00:58:35Z"},{"alias_kind":"pith_short_12","alias_value":"SVEE2DA43X4K","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_16","alias_value":"SVEE2DA43X4KPJZ3","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_8","alias_value":"SVEE2DA4","created_at":"2026-05-18T12:29:42Z"}],"graph_snapshots":[{"event_id":"sha256:10d4b02fe1eab765842afb941fe850963d613be2a93da91d35c7bc2ee63fef50","target":"graph","created_at":"2026-05-18T00:58:35Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"For decades, the growth and volume of digital data collection has made it challenging to digest large volumes of information and extract underlying structure. Coined 'Big Data', massive amounts of information has quite often been gathered inconsistently (e.g from many sources, of various forms, at different rates, etc.). These factors impede the practices of not only processing data, but also analyzing and displaying it in an efficient manner to the user. Many efforts have been completed in the data mining and visual analytics community to create effective ways to further improve analysis and ","authors_text":"Andrew Moran, Jeremy Kepner, Matthew Hubbell, Vijay Gadepally","cross_cats":["cs.CY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2015-06-29T17:50:20Z","title":"Improving Big Data Visual Analytics with Interactive Virtual Reality"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1506.08754","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:d6c8bbf2d454572dd3683026ddb1de7278ccd018a93f25fc0bb5b48ec4cdf816","target":"record","created_at":"2026-05-18T00:58:35Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"7959189787e87702e68fe49c2838e24613c1ca05222f3e572cd68bcc4d3e01da","cross_cats_sorted":["cs.CY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2015-06-29T17:50:20Z","title_canon_sha256":"e847c3133d15a8568fdc45d171b27b06fe53d5a5cfa8e1785a8731dd17c61ca5"},"schema_version":"1.0","source":{"id":"1506.08754","kind":"arxiv","version":2}},"canonical_sha256":"95484d0c1cddf8a7a73b665b6d1c6ff7a5e9523c395ee325d34898261055c417","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"95484d0c1cddf8a7a73b665b6d1c6ff7a5e9523c395ee325d34898261055c417","first_computed_at":"2026-05-18T00:58:35.389279Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:58:35.389279Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yBcHM5g13LZbtYg7anuDl9xZzaWhROeKFRppRTWkyygBH3Ay6aQ5y3uODIqV6kIDMx5yOephTaLXoaqVKeiDBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:58:35.389927Z","signed_message":"canonical_sha256_bytes"},"source_id":"1506.08754","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d6c8bbf2d454572dd3683026ddb1de7278ccd018a93f25fc0bb5b48ec4cdf816","sha256:10d4b02fe1eab765842afb941fe850963d613be2a93da91d35c7bc2ee63fef50"],"state_sha256":"a8550ecf02ef152fda11428a75ee772b4daf762f696406dd708cca0e23e9f800"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"duERgNYpPsT+3MHogdidcz9ULi7bOkyY2mv6Sh8vHJ7vL3FMMh8pZkDLEe786OjGDXuJS4/UrD4bxPPPuiJQDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T19:18:30.934329Z","bundle_sha256":"c8c4e0dd00205010eaf940e0185557af84fc57159e4daecbc0ccd35c96194bcb"}}